Journal of Scientific Engineering Advances
Open Access • Peer Reviewed • Bi-Monthly
Smart Meter Data Analytics for Loss Reduction in Power Distribution Systems in Nigeria
Abstract
The Nigerian Electricity Supply Industry (NESI) faces high Aggregate Technical, Commercial, and Collection (ATC&C) losses, averaging 35.22% in late 2024. This research proposes a framework leveraging smart meter data analytics to identify and mitigate these losses. By using high-frequency data from Advanced Metering Infrastructure (AMI), the study distinguishes between technical and non-technical losses (NTL). The methodology integrates machine learning (Random Forest, SVM) with load flow analysis. Findings provide a strategic roadmap for Distribution Companies (DisCos) to transition from reactive to proactive loss reduction, enhancing revenue and supply reliability.
Copyright & License
© 2026 The Author(s). Published by WM Journals.
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.